• DocumentCode
    247275
  • Title

    Acceleration of the finite element method using hybrid OpenMP-CUDA

  • Author

    Huan-Ting Meng ; Bao-Lin Nie ; Jian-Ming Jin ; Wong, Simon ; Macon, Charles

  • Author_Institution
    Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1379
  • Lastpage
    1380
  • Abstract
    Graphics processing units (GPUs) are efficient in accelerating algorithms that are highly parallelizable. This paper discusses various aspects of parallelizing the traditional finite element algorithm, whose communication-intensive nature makes it difficult to be parallelized in a straightforward manner, and proposes solutions to alleviate the acceleration bottlenecks. The examples show that decent speedup can still be achieved over OpenMP-enabled CPUs.
  • Keywords
    finite element analysis; graphics processing units; parallel architectures; GPU; OpenMP-enabled CPU; accelerating algorithms; communication-intensive nature; finite element method; graphics processing units; hybrid OpenMP-CUDA; Acceleration; Assembly; Finite element analysis; Graphics processing units; Jacobian matrices; Memory management; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas and Propagation Society International Symposium (APSURSI), 2014 IEEE
  • Conference_Location
    Memphis, TN
  • ISSN
    1522-3965
  • Print_ISBN
    978-1-4799-3538-3
  • Type

    conf

  • DOI
    10.1109/APS.2014.6905015
  • Filename
    6905015